auu (). 2. Suppose next that we have even less knowledge of our patient, and we are only given the accuracy of the blood test and prevalence of the disease in our population. We are told that the blood test is 9# percent reliable, this means that the test will yield an accurate positive result in 9#% of the cases where the disease is actually present. Gestational diabetes affects #+1 percent of the population in our patient's age group, and that our test has a false positive rate of #+4 percent. Use your knowledge of Bayes' Theorem and Conditional Probabilities to compute the following quantities based on the information given only in part 2: a. If 100,000 people take the blood test, how many people would you expect to test digbates?
auu (). 2. Suppose next that we have even less knowledge of our patient, and we are only given the accuracy of the blood test and prevalence of the disease in our population. We are told that the blood test is 9# percent reliable, this means that the test will yield an accurate positive result in 9#% of the cases where the disease is actually present. Gestational diabetes affects #+1 percent of the population in our patient's age group, and that our test has a false positive rate of #+4 percent. Use your knowledge of Bayes' Theorem and Conditional Probabilities to compute the following quantities based on the information given only in part 2: a. If 100,000 people take the blood test, how many people would you expect to test digbates?
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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Question
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AaBbCcD AaBbCcD AaBbC AABBCCC AaB
1 No Spac. Heading 1 Heading 2
As
O Re
1 Normal
Title
A Se
Paragraph
Styles
Ed
auu (L).
2. Suppose next that we have even less knowledge of our patient, and we are only given the
accuracy of the blood test and prevalence of the disease in our population. We are told
that the blood test is 9# percent reliable, this means that the test will yield an accurate
positive result in 9#% of the cases where the disease is actually present. Gestational
diabetes affects #+1 percent of the population in our patient's age group, and that our test
has a false positive rate of #+4 percent. Use your knowledge of Bayes' Theorem and
Conditional Probabilities to compute the following quantities based on the information
given only in part 2:
a. If 100,000 people take the blood test, how many people would you expect to test
positive and actually have gestational diabetes?
b. What is the probability of having the disease given that you test positive?
c. If 100,000 people take the blood test, how many people would you expect to test
negative despite actually having gestational diabetes?
d. What is the probability of having the disease given that you tested negative?
e. Comment on what you observe in the above computations. How does the
prevalence of the disease affect whether the test can be trusted?
Fill in the conditional probability table here, then answer the questions in each part
below.
B.
%23"
Transcribed Image Text:Fir
AaBbCcD AaBbCcD AaBbC AABBCCC AaB
1 No Spac. Heading 1 Heading 2
As
O Re
1 Normal
Title
A Se
Paragraph
Styles
Ed
auu (L).
2. Suppose next that we have even less knowledge of our patient, and we are only given the
accuracy of the blood test and prevalence of the disease in our population. We are told
that the blood test is 9# percent reliable, this means that the test will yield an accurate
positive result in 9#% of the cases where the disease is actually present. Gestational
diabetes affects #+1 percent of the population in our patient's age group, and that our test
has a false positive rate of #+4 percent. Use your knowledge of Bayes' Theorem and
Conditional Probabilities to compute the following quantities based on the information
given only in part 2:
a. If 100,000 people take the blood test, how many people would you expect to test
positive and actually have gestational diabetes?
b. What is the probability of having the disease given that you test positive?
c. If 100,000 people take the blood test, how many people would you expect to test
negative despite actually having gestational diabetes?
d. What is the probability of having the disease given that you tested negative?
e. Comment on what you observe in the above computations. How does the
prevalence of the disease affect whether the test can be trusted?
Fill in the conditional probability table here, then answer the questions in each part
below.
B.
%23
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